Course Offerings — Winter Term 2026/2027
Note: This page might not yet list all course offerings before the lecturing period begins, though our offerings are usually stable. If a course is missing, it’s likely due to delays in our internal teaching assignment or by the course organizers. For questions, please contact previous term course organizers (see here).
How to choose your modules
Each MSc main module (ML 1, ML 2, DL 1, DL 2) comes in a standard variant (9 CP) and an -X variant (+3 CP) that adds one elective. CA (BSc) includes one elective. Electives only count as part of an -X module or CA, not standalone. Note: PyML is now called MLE.
Which electives fit which module? (WiSe 2026 offering; electives count only as the +3 CP part of an -X module or of CA)
TODO
Recommended paths
- BSc: start with CA
- MSc:
- No CS background: take introductory CS elsewhere
- Little math background: take introductory math first elsewhere, plan MathML as your elective
- Little engineering background: take MLE
- Solid math/engineering background: take ML/DL (advanced ML) or MLE (advanced engineering)
- Projects: complete ML or DL and MLE first (or equivalent)
Modules
Machine Learning Engineering (MLE)
| Language | English | |
| Organizers | Jannik Wolff and others | |
| Contact | pyml(∂)ml.tu-berlin.de | |
| ISIS | Link (you can visit parts of the course as a guest without an ISIS account) | |
| Credit Points | 6 CP |
This module was renamed from “Python for Machine Learning” to “Machine Learning Engineering” in the winter term 2026/2027. Students who passed PyML cannot take MLE, because both are the same module.